A Comparative Study of the Classical and Bayesian Methods of Estimating a Just-Identified Simultaneous Equations Econometric Model

D. M. Okewole, O. E. Olubusoye, D.K Shangodoyin

Abstract

A just identified two-equation econometric model is simulated using both Classical and Bayesian procedures. The estimates of the parameters for both methods were compared under a wide range of scenarios; sample size, residual variance and variance of the data on the predetermined variable. The Monte Carlo experiment was performed using E-veiws and WinBUGS computer softwares. The median, being a robust estimator of average in terms of validity, was used as the posterior estimate. As indicated in similar research in the past where the posterior mode was used as estimate, the Bayesian procedure performed better in most cases, while some scenarios showed similar behavior for the two procedures.

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